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Recent work has proposed the use of a composite hypothesis Hoeffding test for statistical anomaly detection. Setting an appropriate threshold for the test given a desired false alarm probability involves approximating the false alarm…

Information Theory · Computer Science 2016-09-19 Jing Zhang , Ioannis Ch. Paschalidis

We establish the asymptotic distribution of likelihood ratio tests (LRTs) in settings where some of the nuisance parameters are unidentifiable under the null hypothesis, parameters of interest lie on the boundary of the parameter space, and…

Statistics Theory · Mathematics 2026-05-13 Karl Oskar Ekvall , Ola Hössjer , Matteo Bottai , J. M. Patrik Albin

In this article, the outlier production mechanism of the conventional Multiple Signal Classification (MUSIC) and the g-MUSIC Direction-of-Arrival (DoA) estimation technique is investigated using tools from Random Matrix Theory (RMT). A…

Signal Processing · Electrical Eng. & Systems 2024-10-28 David Schenck , Xavier Mestre , Marius Pesavento

We study the asymptotic spectral behavior of high-dimensional random Gram matrices with sparsity and a variance profile, motivated by applications in wireless communications. Specifically, we consider the Gram matrices $\mathbf S_n=\mathbf…

Statistics Theory · Mathematics 2026-02-10 Rui Wang , Guangming Pan , Dandan Jiang

This study derives a new property of the Wishart distribution when the degree-of-freedom and the size of the matrix parameter of the distribution grow simultaneoulsy. Particularly, the asymptotic normality of the product of four independent…

Statistics Theory · Mathematics 2022-03-29 Koji Tsukuda , Shun Matsuura

Spectrum estimation is a fundamental methodology in the analysis of time-series data, with applications including medicine, speech analysis, and control design. The asymptotic theory of spectrum estimation is well-understood, but the theory…

Statistics Theory · Mathematics 2023-08-15 Andrew Lamperski

We prove two theorems related to the Central Limit Theorem (CLT) for Martin-L\"of Random (MLR) sequences. Martin-L\"of randomness attempts to capture what it means for a sequence of bits to be "truly random". By contrast, CLTs do not make…

Probability · Mathematics 2022-01-31 Anton Vuerinckx , Yves Moreau

We introduce a rigorous and sensitive significance test for hyperuniformity that yields reliable results even from a single sample. Our approach is based on a detailed analysis of the empirical Fourier transform of a stationary point…

Statistics Theory · Mathematics 2026-03-23 Michael A. Klatt , Günter Last , Norbert Henze

If the log likelihood is approximately quadratic with constant Hessian, then the maximum likelihood estimator (MLE) is approximately normally distributed. No other assumptions are required. We do not need independent and identically…

Statistics Theory · Mathematics 2012-07-06 Charles J. Geyer

Datasets from the fields of bioinformatics, chemometrics, and face recognition are typically characterized by small samples of high-dimensional data. Among the many variants of linear discriminant analysis that have been proposed in order…

Machine Learning · Statistics 2020-04-20 Lama B. Niyazi , Abla Kammoun , Hayssam Dahrouj , Mohamed-Slim Alouini , Tareq Y. Al-Naffouri

Nonparametric two-stage procedures to construct fixed-width confidence intervals are studied to quantify uncertainty. It is shown that the validity of the random central limit theorem (RCLT) accompanied by a consistent and asymptotically…

Statistics Theory · Mathematics 2019-10-08 Yuan-Tsung Chang , Ansgar Steland

The Plackett--Luce model has been extensively used for rank aggregation in social choice theory. A central statistical question in this model concerns estimating the utility vector that governs the model's likelihood. In this paper, we…

Statistics Theory · Mathematics 2025-05-09 Ruijian Han , Yiming Xu

Stochastic gradient algorithms are more and more studied since they can deal efficiently and online with large samples in high dimensional spaces. In this paper, we first establish a Central Limit Theorem for these estimates as well as for…

Statistics Theory · Mathematics 2017-10-17 Antoine Godichon-Baggioni

We consider the hyperuniform model of d-dimensional integer lattice perturbed by independent random variables and we investigate the large scale asymptotic fluctuations of smoothed versions of the usual counting statistics, specifically of…

Probability · Mathematics 2025-03-05 Gabriel Mastrilli

We generalize classical results in spectral graph theory and linear algebra more broadly, from the case where the underlying matrix is Hermitian to the case where it is non-Hermitian. New admissibility conditions are introduced to replace…

Spectral Theory · Mathematics 2019-05-21 Edinah K. Gnang , James M. Murphy

We present experimental and theoretical results for the fluctuation properties in the incomplete spectra of quantum systems with symplectic symmetry and a chaotic dynamics in the classical limit. To obtain theoretical predictions, we extend…

Quantum Physics · Physics 2021-05-11 Jiongning Che , Junjie Lu , 2 Xiaodong Zhang , 1 Barbara Dietz , Guozhi Chai

In previous papers, we studied the asymptotic behaviour of $S_N(A,X)=(2N+1)^{-d/2}\sum_{n \in A_N} X_n,$ where $X$ is a centered, stationary and weakly dependent random field, and $A_N=A \cap [-N,N]^d$, $A \subset \mathbb{Z}^d$. This leads…

Methodology · Statistics 2009-11-06 Beatriz Marron , Ana Tablar

In this paper we show a functional central limit theorem for the sum of the first $\lfloor t n \rfloor$ diagonal elements of $f(Z)$ as a function in $t$, for $Z$ a random real symmetric or complex Hermitian $n\times n$ matrix. The result…

Probability · Mathematics 2019-07-22 Jan Nagel

We study the behavior of infinite systems of coupled harmonic oscillators as t->infinity, and generalize the Central Limit Theorem (CLT) to show that their reduced Wigner distributions become Gaussian under quite general conditions. This…

General Relativity and Quantum Cosmology · Physics 2009-10-22 Max Tegmark , Harold S. Shapiro

We place ourselves in the setting of high-dimensional statistical inference, where the number of variables $p$ in a data set of interest is of the same order of magnitude as the number of observations $n$. More formally, we study the…

Probability · Mathematics 2009-12-11 Noureddine El Karoui